Return default prompt.
pydantic model langchain.agents.SelfAskWithSearchChain[source]#
Chain that does self ask with search.
Example
from langchain import SelfAskWithSearchChain, OpenAI, GoogleSerperAPIWrapper
search_chain = GoogleSerperAPIWrapper()
self_ask = SelfAskWithSearchChain(llm=OpenAI(), search_chain=search_chain)
Validators
set_callback_manager » callback_manager
set_verbose » verbose
validate_tools » all fields
field agent: Agent [Required]#
field callback_manager: BaseCallbackManager [Optional]#
field early_stopping_method: str = 'force'#
field max_iterations: Optional[int] = 15#
field memory: Optional[BaseMemory] = None#
field return_intermediate_steps: bool = False#
field tools: Sequence[BaseTool] [Required]#
field verbose: bool [Optional]#
pydantic model langchain.agents.Tool[source]#
Tool that takes in function or coroutine directly.
Validators
set_callback_manager » callback_manager
field coroutine: Optional[Callable[[str], Awaitable[str]]] = None#
field description: str = ''#
field func: Callable[[str], str] [Required]#
pydantic model langchain.agents.ZeroShotAgent[source]#
Agent for the MRKL chain.
field allowed_tools: Optional[List[str]] = None#
field llm_chain: langchain.chains.llm.LLMChain [Required]#
field return_values: List[str] = ['output']#